TY - GEN
T1 - How does the shape descriptor measure the perceptual quality of the retargeting image?
AU - Ma, Lin
AU - Xu, Long
AU - Zeng, Huanqiang
AU - Ngan, King N.
AU - Deng, Chenwei
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/9/3
Y1 - 2014/9/3
N2 - Perceptual quality evaluation of the retargeting image plays an important role in benchmarking different retargeting methods, as well as guiding or optimizing the retargeting process. The distortions introduced during the retargeting process are mainly categorized into shape distortion and content information loss [1]. The shape distortion measurement is critical to the evaluation of retargeting image perceptual quality. In this paper, the performances of different shape descriptors, such as PHOW [2], GIST [3], MPEG-7 descriptors [4], EMD [5], for evaluating the perceptual quality of the retargeting image are examined based on the public image retargeting subjective quality database [6]. Experimental results demonstrated that most of the shape descriptors can hardly capture the characteristics representing the quality of the retargeting image, but the global shape descriptor GIST [3] presents significant performance gains. Moreover, by incorporating with the measurements from the perspective of content information loss, a better performance is further obtained.
AB - Perceptual quality evaluation of the retargeting image plays an important role in benchmarking different retargeting methods, as well as guiding or optimizing the retargeting process. The distortions introduced during the retargeting process are mainly categorized into shape distortion and content information loss [1]. The shape distortion measurement is critical to the evaluation of retargeting image perceptual quality. In this paper, the performances of different shape descriptors, such as PHOW [2], GIST [3], MPEG-7 descriptors [4], EMD [5], for evaluating the perceptual quality of the retargeting image are examined based on the public image retargeting subjective quality database [6]. Experimental results demonstrated that most of the shape descriptors can hardly capture the characteristics representing the quality of the retargeting image, but the global shape descriptor GIST [3] presents significant performance gains. Moreover, by incorporating with the measurements from the perspective of content information loss, a better performance is further obtained.
KW - Perceptual quality assessment
KW - content information loss
KW - retargeting image
KW - shape descriptor
KW - shape distortion
UR - http://www.scopus.com/inward/record.url?scp=84937113078&partnerID=8YFLogxK
U2 - 10.1109/ICMEW.2014.6890548
DO - 10.1109/ICMEW.2014.6890548
M3 - Conference contribution
AN - SCOPUS:84937113078
T3 - 2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014
BT - 2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2014
Y2 - 14 July 2014 through 18 July 2014
ER -